ملخص
Robust design (RD) is a popular design methodology for minimizing the variability of product performance, thereby, improving the quality of a product. Although RD principles have been widely implemented in many industries, and a number of new RD models have been reported in the literature, there is ample room for improvement. First, a number of RD models consider a single quality characteristic (QC). In reality, however, the judgmental basis of a product from the perspective of the customer is characterized by the assessment of multiple QCs, which are often correlated. Second, previous models often fail to emphasize customer preferences in the modeling and optimization phases. To rectify these shortcomings, this paper proposes a compromise programming model for synthesizing Pareto solutions that represent compromised trade-offs between multiple correlated QCs based on the customer's preferences. The Tchebycheff-metric-based compromise programming method employed to determine Pareto solutions is superior to the simplistic weighted sum and goal programming approaches that may fail to explore the full set of Pareto points for a multi-objective optimization problem.
اللغة الأصلية | English |
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الصفحات (من إلى) | 423-433 |
عدد الصفحات | 11 |
دورية | International Journal of Advanced Manufacturing Technology |
مستوى الصوت | 32 |
رقم الإصدار | 5-6 |
المعرِّفات الرقمية للأشياء | |
حالة النشر | Published - مارس 2007 |
منشور خارجيًا | نعم |
ASJC Scopus subject areas
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